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  1. Results that match 2 of 3 words

  2. williams2006POMDPsForSDSs-manuscript

    mi.eng.cam.ac.uk/~sjy/papers/wiyo07.pdf
    20 Feb 2018: policy. In the regions of belief space close to the corners (where certainty is high), the policy chooses doSave or doDelete; in the middle of belief space (where certainty is low)
  3. LOGOTHETIS ET AL.: A CNN BASED APPROACH FOR THE ...

    mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2020-BMVC-CNN-NF-Photometric-Stereo.pdf
    28 Jun 2021: As the depth will onlybe approximately known at test time, this is slightly perturbed before mappingresulting to a structured change of the map (shown at bottom left: middle is actualdepth (10 ... In order to solve the near-field PS problem for aspecific
  4. Contour-Based Learning for Object Detection Jamie ShottonDepartment…

    mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2005-ICCV-Shotton-object-detection.pdf
    13 Mar 2018: Test-ing was performed on 164 images containing 193 cars,and164 background images. ... Our technique relies on edge features andhigher-resolution training and test images would certainlyimprove results.
  5. main.dvi

    mi.eng.cam.ac.uk/~cipolla/archive/Publications/article/2011-PAMI-3D-Faces.pdf
    13 Mar 2018: to test our hypothesis. Therefore the problem of detecting. shadows becomes more difficult. ... The shading regularization scheme shows a smooth surface. (Fig. 5 middle) while the shape regularization scheme (Fig.
  6. Semantic Transform: Weakly Supervised Semantic Inference for Relating …

    mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2013-ICCV-Shankar-attrirbutes.pdf
    13 Mar 2018: Givena test image with its feature vector xt, its score for attributeam is given by ϕ(bTm, xt). ... Absolute Classification: This refers to the task of as-signing a test image to its correct class.
  7. Face Recognition with Image Sets Using Manifold Density Divergence ...

    mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2005-CVPR-Arandjelovic-divergence.pdf
    13 Mar 2018: These meth-ods have achieved very good accuracy on a small number ofcontrolled test sets. ... We therefore useDKL(p(0)||p(i)) as a “distance measure” between trainingand test sets.
  8. Uniform precision ultrasound strain imaging G.M. Treece, J.E. Lindop, …

    mi.eng.cam.ac.uk/reports/svr-ftp/treece_tr624.pdf
    9 Mar 2009: The remaining images show lightlyfiltered (middle row) and heavily filtered (bottom row) versions of the strain data. ... The remainingimages show lightly filtered (middle row) and heavily filtered (bottom row) versions of the straindata.
  9. PX-NET: Simple and Efficient Pixel-Wise Trainingof Photometric Stereo …

    mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2021-ICCV-PX-NET-photometric-normals.pdf
    9 Apr 2022: performs realistic computation of global illumination ef-fects. The first dataset is Cycles-PS-Test [16] containing 3objects. ... For completeness, we also in-clude the results after applying the test time rotation pseudo-invariance augmentation (K=10).
  10. Reducing Word Error Rates of Found Speech -XPERT Tool ...

    mi.eng.cam.ac.uk/reports/svr-ftp/johnson_tr330.pdf
    10 Apr 2000: Middle-clicking on a word in the recogniser output focuses on the word plus two words of context oneither side, giving 5 words in total. ... The speech is spontaneous and suffersfrom a large variation in speaker rate, with un-natural gaps in the middle
  11. A Pose-Wise Linear Illumination Manifold Model for Face Recognition…

    mi.eng.cam.ac.uk/~cipolla/publications/article/2007_CVIU_paper2.pdf
    13 Mar 2018: also see [27]). In AFR tests, such methods are usually outperformed by meth-. ... the data as test input. In all tests, both training data for each person in the gallery,.

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